National University of Singapore, CS4243: Computer Vision and Pattern Recognition, lab group B4.
# Activate the conda env
conda activate CS4243
# Run the notebooks in Chrome
jupyter notebook
# Run the test.ipynb
# Do all of these in the terminal
# Conda installation
curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o miniconda.sh -J -L -k
chmod +x miniconda.sh
./miniconda.sh
# Clone GitHub repo
git clone https://github.com/li-chuan-1998/CS4243.git
cd CS4243
# Install python libraries
conda env create -f environment_mac_x86.yml
# Activate the environment
conda activate CS4243
# Run the notebooks in Chrome
jupyter notebook
This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):
Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:01:00)
[Clang 13.0.1 ]
Tensorflow Version: 2.9.2
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0
# Do all of these in the terminal
# Miniforge donwload
curl https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh -O
chmod +x Miniforge3-MacOSX-arm64.sh
./Miniforge3-MacOSX-arm64.sh
# Clone GitHub repo
git clone https://github.com/li-chuan-1998/CS4243.git
cd CS4243
# Install python libraries
conda env create -f environment_mac_arm.yml
# Activate the environment
conda activate CS4243
# Run the notebooks in Chrome
jupyter notebook
This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):
Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:00:52)
[Clang 13.0.1 ]
Tensorflow Version: 2.9.1
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0
# Install Anaconda
https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe
# Open an Anaconda Terminal
Go to Application => Anaconda3 => Anaconda Cmd Prompt
# Install git & clone repo: Type in terminal
conda install git
git clone https://github.com/li-chuan-1998/CS4243.git
cd CS4243
# Install python libraries
conda env create -f environment_win10.yml
conda activate CS4243
# Run the notebooks in Chrome
jupyter notebook
This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):
Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:50:36) [MSC v.1929 64 bit (AMD64)]
Tensorflow Version: 2.9.0
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0
# Install Anaconda
https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe
# Open an Anaconda Terminal
Go to Application => Anaconda3 => Anaconda Cmd Prompt
# Install git & clone repo: Type in terminal
conda install git
git clone https://github.com/li-chuan-1998/CS4243.git
cd CS4243
# Install python libraries
conda env create -f environment_win10_gpu.yml
conda activate CS4243
# Run the notebooks in Chrome
jupyter notebook
This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):
Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:50:36) [MSC v.1929 64 bit (AMD64)]
Tensorflow Version: 2.9.0
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0
https://docs.google.com/presentation/d/16JJ6KmhWDtNLMeveXpdKm7Vs_yKaiPNQKth9P-_BaSs/edit?usp=sharing